Alan Louis Scheinine wrote:
> This thread has moved to the question of utilization,
> discussed by Mark Hahn, Gus Correa and Håkon Bugge.
> In my previous job most people developed code, though test runs
> could run for days and use as many as 64 cores. It was
> convenient for most people to have immediate access due to
> the excess computation capacity whereas some people in top
> management wanted maximum utilization.
>> I was at a parallel computing workshop where other people
> described the contrast between their needs and the goals of
> their computer centers. The computer centers wanted maximum
> utilization whereas the spare capacity of the various clusters
> in the labs were especially useful for the researchers. They
> could bring to bear the computational power of their informally
> administered clusters for special tasks such as when a huge
> block of data needed to be analyzed in nearly realtime to see
> if an experiment of limited duration was going well.
>> When most work involves code development, waiting for jobs in
> a batch queue means that the human resources are not being
> used efficiently. Of course, maximum utilization of computer
> resources is necessary for production code, I just want to
> emphasize the wide range of needs.
>> I would like to add that maximum utilization and fast turn-
> around are contradictory goals, it would seem to me based
> on the following reasoning. Consider packing a truck with
> boxes where the heigth of the boxes represents the number
> of cores and the width of the boxes represents the time of
> execution (leaving aside third spatial dimension). To most
> efficiently solve the packing problem we would like to have
> all boxes visible on the loading dock before we start packing.
> On the other hand, if boxes arrive a few at a time and we must
> put the boxes into the truck as they arrive (low queue wait time)
> then the packing will not be efficient. Moreover, as a very
> rough estimate, the size of the box defines the scale of the
> problem, specifically, if the average running time is 4 hours,
> then to have efficient "packing" the time spent waiting in a
> queue must on the order of at least 4 and more likely 8 hours
> in order to have enough requests visible to be able to find
> an efficient solution to the scheduling problem.
An interesting analogy, and further, the thread has been interesting.
However, it doesn't even begin to really address near-realtime
processing requirements. Examples of these are common in the weather
modeling I'm engaged in. In some cases, looking at severe weather and
predictive models, a model needs to initiate shortly after a watch or
warning is issued, something that's controlled by humans and is not
scheduled, hence somewhat difficult to model for job scheduling. These
models would likely be re-run with new data assimilated into the
forcings, and a new solution produced. Similarly, models of toxic
release plumes are unscheduled events with a high priority and low
queue-wait time requirement.
Other weather models are more predictable but have fairly hard
requirements for when output must be available.
Conventional batch scheduling handles these conditions pretty poorly. A
full queue with even reasonable matching of available cores to request
isn't likely to get these jobs out very quickly on a loaded system.
Preemption is the easy answer but unpopular with administrators who have
to answer the phone, users whose jobs are preempted (some never to see
their jobs return), and the guy who's the preemptor... who gets blamed
for all the problems. Worse, arbitrary preemption assignment means
someone made a value judgment that someone's science is more important
than someone else's, a sure plan for troubles when the parties all
gather somewhere... like a faculty meeting.
OK, so I've laid out a piece of the problem. I've got some ideas on
solutions, and avenues for investigation to address these but I'd like
to see others ideas. I don't want to influence the outcome any mroe
than I already have.
Oh, and, yeah, I'm aware of SPRUCE but I see a few potential problems
there, although that framework has some potential.
gc
--
Gerry Creager -- gerry.creager at tamu.edu
Texas Mesonet -- AATLT, Texas A&M University
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